KMS Institute Of Geographic Sciences And Natural Resources Research,CAS
Mapping hourly dynamics of urban population using trajectories reconstructed from mobile phone records | |
Liu, Zhang1,2; Ma, Ting1,2![]() ![]() ![]() | |
2018-04-01 | |
Source Publication | TRANSACTIONS IN GIS
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ISSN | 1361-1682 |
Volume | 22Issue:2Pages:494-513 |
Corresponding Author | Ma, Ting(mting@lreis.ac.cn) |
Abstract | Understanding the spatiotemporal dynamics of urban population is crucial for addressing a wide range of urban planning and management issues. Aggregated geospatial big data have been widely used to quantitatively estimate population distribution at fine spatial scales over a given time period. However, it is still a challenge to estimate population density at a fine temporal resolution over a large geographical space, mainly due to the temporal asynchrony of population movement and the challenges to acquiring a complete individual movement record. In this article, we propose a method to estimate hourly population density by examining the time-series individual trajectories, which were reconstructed from call detail records using BP neural networks. We first used BP neural networks to predict the positions of mobile phone users at an hourly interval and then estimated the hourly population density using log-linear regression at the cell tower level. The estimated population density is linearly correlated with population census data at the sub-district level. Trajectory clustering results show five distinct diurnal dynamic patterns of population movement in the study area, revealing spatially explicit characteristics of the diurnal commuting flows, though the driving forces of the flows need further investigation. |
DOI | 10.1111/tgis.12323 |
WOS Keyword | BIG DATA ; BUILDING-LEVEL ; PATTERNS ; DISTRIBUTIONS ; BEHAVIOR ; HOTSPOTS ; NETWORK ; SPACE ; AREAS |
Indexed By | SCI |
Language | 英语 |
Funding Project | National Natural Science Foundation of China[4159840011] ; National Natural Science Foundation of China[41771418] ; Foundation for Innovative Research Groups of the National Natural Science Foundation of China[41421001] ; State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences[088RA500PA] ; Institute of Geographic Sciences and Natural Resources Research, CAS[2014RC102] |
Funding Organization | National Natural Science Foundation of China ; Foundation for Innovative Research Groups of the National Natural Science Foundation of China ; State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences ; Institute of Geographic Sciences and Natural Resources Research, CAS |
WOS Research Area | Geography |
WOS Subject | Geography |
WOS ID | WOS:000430399600007 |
Publisher | WILEY |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.igsnrr.ac.cn/handle/311030/57299 |
Collection | 中国科学院地理科学与资源研究所 |
Corresponding Author | Ma, Ting |
Affiliation | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, 11A Datun Rd, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China |
Recommended Citation GB/T 7714 | Liu, Zhang,Ma, Ting,Du, Yunyan,et al. Mapping hourly dynamics of urban population using trajectories reconstructed from mobile phone records[J]. TRANSACTIONS IN GIS,2018,22(2):494-513. |
APA | Liu, Zhang,Ma, Ting,Du, Yunyan,Pei, Tao,Yi, Jiawei,&Peng, Hui.(2018).Mapping hourly dynamics of urban population using trajectories reconstructed from mobile phone records.TRANSACTIONS IN GIS,22(2),494-513. |
MLA | Liu, Zhang,et al."Mapping hourly dynamics of urban population using trajectories reconstructed from mobile phone records".TRANSACTIONS IN GIS 22.2(2018):494-513. |
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